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Optimised mobile reasoning for pervasive service discovery

Optimised mobile reasoning for pervasive service discovery

引用

IEEE International Conference on Web Services, ICWS 2008

作者： Steller, Luke Krishnaswamy, Shonali Centre for Distributed Systems and Software Engineering Monash University Melbourne Australia

ISBN: (纸本)9780769533100

Today's mobile users have access to a wide range of web-based services. This paper presents our m-Tableaux algorithm for enabling cost-efficient and optimised semantic reasoning to support pervasive service discovery. We present performance evaluation of the m-Tableaux optimisation strategies which clearly demonstrate its operational feasibility on a mobile device. © 2008 IEEE.

关键词： Semantics

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Resource-aware ECG analysis on mobile devices 11

Resource-aware ECG analysis on mobile devices

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Proceedings of the 2011 ACM Symposium on Applied Computing

作者： Sinha, Abhijat Tayebi, Hossein Krishnaswamy, Shonali Waluyo, Agustinus Borgy Gaber, Mohamed Medhat Centre for Distributed Systems and Software Engineering Monash University Australia University of Portsmouth United Kingdom

ISBN: (纸本)9781450301138

关键词： Time series analysis

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distributed data stream classification for wireless sensor networks 10

Distributed data stream classification for wireless sensor n...

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25th Annual ACM Symposium on Applied Computing, SAC 2010

作者： Gaber, Mohamed Medhat Shiddiqi, Ary Mazharuddin Centre for Distributed Systems and Software Engineering Monash University Australia Clayton School of Information Technology Monash University Australia

ISBN: (纸本)9781605586380

It has been established experimentally that in-network processing in wireless sensor networks is the acceptable mode of operation. However, this solution is faced by resource constraints of the sensor nodes, especially when running traditional data mining techniques that tend to consume the resources rapidly. On the other hand, data stream mining algorithms still fall short with the limited computational capabilities of the nodes. These algorithms need real-time adaptation to availability of resources. distributed processing is also essential to produce a global model of the data streams emanated from the network. In this paper, we propose a novel distributed data stream classification technique that is able to adapt to availability of resources in wireless sensor networks. © 2010 ACM.

关键词： Classification (of information)

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Congestion avoidance algorithm using extended kalman filter

Congestion avoidance algorithm using extended kalman filter

引用

2nd International Conference on Convergent Information Technology, ICCIT 07

作者： Kim, Sung-Soo Kang, Yong-Bin Digital Content Research Division ETRI Korea Republic of Centre for Distributed Systems and Software Engineering Monash University Australia

ISBN: (纸本)0769530389

The prediction of traffic congestion is quite an important issue in vehicle navigation to smoothly control traffic flow, and improve the quality of driver's convenience. However, it is not easy to make accurate predictions since traffic change is highly nonlinear and complex dynamic process. First, we present a new traffic prediction algorithm on the basis of the combined knowledge of both the historical and the real-time traffic information. Based on this traffic prediction result, this paper presents a novel routing technique capable of providing intelligent route services completely adequate to dynamic route guidance systems. In our experiments, we have performed the proposed algorithms on two road networks;one of the complex urban areas and the city. Overall, the results of traffic prediction indicate that our prediction algorithms provide more accurate (nearly 90%) traffic information compared with previous traffic prediction solutions. In addition, our implementation of route determination provides the adaptive routes for traffic conditions, as well as scalable routing services for users' preferences. © 2007 IEEE.

关键词： Extended Kalman filters

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Role of context-awareness for demand response mechanisms

引用

Lecture Notes in Computer Science

作者： Haghighi, Pari Delir Krishnaswamy, Shonali Centre for Distributed Systems and Software Engineering Monash University 900 Dandenong Rd Caulfield East VIC 3145 Australia

ISBN: (纸本)9783642234460

Recently due to major changes in the structure of electricity industry and the rising costs of power generation, many countries have realized the potential and benefits of smart metering systems and demand response programs in balancing between the supply and the demand. DR mechanisms are capable of controlling the user energy consumption according to load conditions and providing effective energy management. However, they are typically performed regardless of user's situation and current activities. Factoring in the user's contextual information which is relevant to their current or future energy consumption can significantly increase the effectiveness of DR programs and enable adaptive and personalized execution of DR control actions. In this paper, we review current DR techniques and discuss the state-of-the-art smart energy management approaches that take into account contextual information. An overview of context reasoning and learning techniques for smart homes are presented to demonstrate how knowledge of user activities can be utilized in context-aware DR mechanisms. Our aim is to provide a better understanding of DR programs and highlight the importance of the context-awareness in improving smart energy management. © 2011 Springer-Verlag.

关键词： Energy management

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Test order for class-based integration testing of Java applications

Test order for class-based integration testing of Java appli...

引用

5th International Conference on Quality software, QSIC 2005

作者： Hashim, Nor Laily Schmidt, Heinz W. Ramakrishnan, Sita Centre for Distributed Systems and Software Engineering Monash University 900 Dandenong Road Caulfield Vic. 3145 Australia

ISBN: (纸本)0769524729

This paper presents an improvement to existing class test ordering stategies by including coupling measures to reduce non-determinism and decrease the number of stubs to be produced. Our novel strategy aims to lift the known methods from class hierarchies to component-based product lines in which so-called connectors between components are key entities for structuring, assembling and integrating software architectures, and in which tighter coupling of classes inside components and looser coupling between classes in different components are fundamental to component-based architecture composition. The paper also evaluates the new method and confirms the expected reductions in the number of stubs generated and the improved test ordering. Two recent test order strategies for C++ are compared with our novel approach through experiments conducted on two mini product lines written in Java. The new proposed test ordering strategy is more deterministic through measuring coupling, which is at the heart of component-based product line architectures. © 2005 IEEE.

关键词： Java programming language

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Soilse: A decentralized approach to optimization of fluctuating urban traffic using reinforcement learning

Soilse: A decentralized approach to optimization of fluctuat...

引用

International IEEE Conference on Intelligent Transportation systems

作者： Salkham, AS'ad Cahill, Vinny Distributed Systems Group School of Computer Science and Statistics Trinity College Dublin Ireland Lero - The Irish Software Engineering Research Centre

ISBN: (纸本)9781424476572

Increasing traffic congestion is a major problem in urban areas, which incurs heavy economic and environmental costs in both developing and developed countries. Efficient urban traffic control (UTC) can help reduce traffic congestion. However, the increasing volume and the dynamic nature of urban traffic pose particular challenges to UTC. Reinforcement Learning (RL) has been shown to be a promising approach to efficient UTC. However, most existing work on RL-based UTC does not adequately address the fluctuating nature of urban traffic. This paper presents Soilse1, a decentralized RL-based UTC optimization scheme that includes a nonparametric pattern change detection mechanism to identify local traffic pattern changes that adversely affect an RL agent's performance. Hence, Soilse is adaptive as agents learn to optimize for different traffic patterns and responsive as agents can detect genuine traffic pattern changes and trigger relearning. We compare the performance of Soilse to two baselines, a fixed-time approach and a saturation balancing algorithm that emulates SCATS, a well-known UTC system. The comparison was performed based on a simulation of traffic in Dublin's inner city centre. Results from using our scheme show an approximate 35%-43% and 40%-54% better performance in terms of average vehicle waiting time and average number of vehicle stops respectively against the best baseline performance in our simulation. ©2010 IEEE.

关键词： Reinforcement learning

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Mining data streams: A review

Mining data streams: A review

引用

作者： Gaber, Mohamed Medhat Zaslavsky, Arkady Krishnaswamy, Shonali Centre for Distributed Systems and Software Engineering Monash University 900 Dandenong Rd. Caulfield East Vic. 3145 Australia

The recent advances in hardware and software have enabled the capture of different measurements of data in a wide range of fields. These measurements are generated continuously and in a very high fluctuating data rates. Examples include sensor networks, web logs, and computer network traffic. The storage, querying and mining of such data sets are highly computationally challenging tasks. Mining data streams is concerned with extracting knowledge structures represented in models and patterns in non stopping streams of information. The research in data stream mining has gained a high attraction due to the importance of its applications and the increasing generation of streaming information. Applications of data stream analysis can vary from critical scientific and astronomical applications to important business and financial ones. Algorithms, systems and frameworks that address streaming challenges have been developed over the past three years. In this review paper, we present the state-of-the-art in this growing vital field.

关键词： Data mining

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RA-SAX: Resource-aware symbolic aggregate approximation for mobile ECG analysis

RA-SAX: Resource-aware symbolic aggregate approximation for ...

引用

2011 12th IEEE International Conference on Mobile Data Management, MDM 2011

作者： Tayebi, Hossein Krishnaswamy, Shonali Waluyo, Augustinus Borgy Sinha, Abhijat Gaber, Mohamed Medhat Centre for Distributed Systems and Software Engineering Monash University Melbourne VIC Australia School of Computing University of Portsmouth Portsmouth United Kingdom

ISBN: (纸本)9780769544366

There is a growing focus on 24/7 cardiac monitoring that leverages state of the art mobile phones and commercial-off-the-shelf (COTS) wearable bio-sensors. While many signal processing techniques for mobile ECG analysis have been developed, these techniques tend to be computationally intensive. In this paper, we propose, develop and evaluate a resource-aware and energy-efficient time series analysis technique for real-time ECG analysis on mobile devices based on the well-known SAX (Symbolic Aggregate Approximation) representation for time series termed RA-SAX. © 2011 IEEE.

关键词： Aggregates

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An approach to data fusion for context awareness

An approach to data fusion for context awareness

引用

5th International and Interdisciplinary Conference CONTEXT 2005 - Modeling and Using Context

作者： Padovitz, Amir Loke, Seng W. Zaslavsky, Arkady Burg, Bernard Bartolini, Claudio Centre for Distributed Systems and Software Engineering 900 Dandenong Rd. Caulfield-East Vic. Australia HP Labs Palo-Alto United States

ISBN: (纸本)354026924X

We propose and develop an approach modeled with multi-attribute utility theory for sensor fusion in context-aware environments. Our approach is distinguished from existing general purpose fusion techniques by a number of factors including a general underlying context model it is built upon and a set of heuristics it covers. The technique is developed for context-aware applications and we argue that it provides various advantages for data fusion in context-aware scenarios. We experimentally evaluate our approach with actual use cases using real sensors. © Springer-Verlag Berlin Heidelberg 2005.

关键词： Sensor data fusion

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